ShapeMOD: Macro Operation Discovery for 3D Shape Programs

A popular way to create detailed yet easily controllable 3D shapes is via procedural modeling, i.e. generating geometry using programs. Such programs consist of a series of instructions along with their associated parameter values. To fully realize the benefits of this representation, a shape program should be compact and only expose degrees of freedom that allow for meaningful manipulation of output geometry. One way to achieve this goal is to design higher-level macro operators that, when executed, expand into a series of commands from the base shape modeling language. However, manually authoring such macros, much like shape programs themselves, is difficult and largely restricted to domain experts. In this paper, we present ShapeMOD, an algorithm for automatically discovering macros that are useful across large datasets of 3D shape programs. ShapeMOD operates on shape programs expressed in an imperative, statement-based language. It is designed to discover macros that make programs more compact by minimizing the number of function calls and free parameters required to represent an input shape collection. We run ShapeMOD on multiple collections of programs expressed in a domain-specific language for 3D shape structures. We show that it automatically discovers a concise set of macros that abstract out common structural and parametric patterns that generalize over large shape collections. We also demonstrate that the macros found by ShapeMOD improve performance on downstream tasks including shape generative modeling and inferring programs from point clouds. Finally, we conduct a user study that indicates that ShapeMOD's discovered macros make interactive shape editing more efficient

Fuzzy min-max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes

Constitutive Type VI Secretion System Expression Gives Vibrio cholerae Intra- and Interspecific Competitive Advantages

The type VI secretion system (T6SS) mediates protein translocation across the cell membrane of Gram-negative bacteria, including Vibrio cholerae – the causative agent of cholera. All V. cholerae strains examined to date harbor gene clusters encoding a T6SS. Structural similarity and sequence homology between components of the T6SS and the T4 bacteriophage cell-puncturing device suggest that the T6SS functions as a contractile molecular syringe to inject effector molecules into prokaryotic and eukaryotic target cells. Regulation of the T6SS is critical. A subset of V. cholerae strains, including the clinical O37 serogroup strain V52, express T6SS constitutively. In contrast, pandemic strains impose tight control that can be genetically disrupted: mutations in the quorum sensing gene luxO and the newly described regulator gene tsrA lead to constitutive T6SS expression in the El Tor strain C6706. In this report, we examined environmental V. cholerae isolates from the Rio Grande with regard to T6SS regulation. Rough V. cholerae lacking O-antigen carried a nonsense mutation in the gene encoding the global T6SS regulator VasH and did not display virulent behavior towards Escherichia coli and other environmental bacteria. In contrast, smooth V. cholerae strains engaged constitutively in type VI-mediated secretion and displayed virulence towards prokaryotes (E. coli and other environmental bacteria) and a eukaryote (the social amoeba Dictyostelium discoideum). Furthermore, smooth V. cholerae strains were able to outcompete each other in a T6SS-dependent manner. The work presented here suggests that constitutive T6SS expression provides V. cholerae with an advantage in intraspecific and interspecific competition.Canadian Institutes of Health Research (Operating Grant MOP-84473)Alberta Heritage Foundation for Medical Research (Alberta Innovates-Health Solutions, Endowment Fund)National Institutes of Health (U.S.) (grant MD001091-01)National Institutes of Health (U.S.) (grant GM068855-02)Olegario V. Rana FellowshipAlberta Heritage Foundation for Medical Research (Alberta Innovates-Health Solutions Graduate Studentships

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD

X-Ray Spectroscopy of Stars

(abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

Crosstalk between Chemokine Receptor CXCR4 and Cannabinoid Receptor CB2 in Modulating Breast Cancer Growth and Invasion

Cannabinoids bind to cannabinoid receptors CB(1) and CB(2) and have been reported to possess anti-tumorigenic activity in various cancers. However, the mechanisms through which cannabinoids modulate tumor growth are not well known. In this study, we report that a synthetic non-psychoactive cannabinoid that specifically binds to cannabinoid receptor CB(2) may modulate breast tumor growth and metastasis by inhibiting signaling of the chemokine receptor CXCR4 and its ligand CXCL12. This signaling pathway has been shown to play an important role in regulating breast cancer progression and metastasis.We observed high expression of both CB(2) and CXCR4 receptors in breast cancer patient tissues by immunohistochemical analysis. We further found that CB(2)-specific agonist JWH-015 inhibits the CXCL12-induced chemotaxis and wound healing of MCF7 overexpressing CXCR4 (MCF7/CXCR4), highly metastatic clone of MDA-MB-231 (SCP2) and NT 2.5 cells (derived from MMTV-neu) by using chemotactic and wound healing assays. Elucidation of the molecular mechanisms using various biochemical techniques and confocal microscopy revealed that JWH-015 treatment inhibited CXCL12-induced P44/P42 ERK activation, cytoskeletal focal adhesion and stress fiber formation, which play a critical role in breast cancer invasion and metastasis. In addition, we have shown that JWH-015 significantly inhibits orthotopic tumor growth in syngenic mice in vivo using NT 2.5 cells. Furthermore, our studies have revealed that JWH-015 significantly inhibits phosphorylation of CXCR4 and its downstream signaling in vivo in orthotopic and spontaneous breast cancer MMTV-PyMT mouse model systems.This study provides novel insights into the crosstalk between CB(2) and CXCR4/CXCL12-signaling pathways in the modulation of breast tumor growth and metastasis. Furthermore, these studies indicate that CB(2) receptors could be used for developing innovative therapeutic strategies against breast cancer